Sarcopenia is characterized by decreased skeletal muscle mass and function with age. Aged muscles have altered lipid compositions; however, the role and regulation of lipids are unknown. Here we report that FABP3 is upregulated in aged skeletal muscles, disrupting homeostasis via lipid remodeling. Lipidomic analyses reveal that FABP3 overexpression in young muscles alters the membrane lipid composition to that of aged muscle by decreasing polyunsaturated phospholipid acyl chains, while increasing sphingomyelin and lysophosphatidylcholine. FABP3-dependent membrane lipid remodeling causes ER stress via the PERK-eIF2α pathway and inhibits protein synthesis, limiting muscle recovery after immobilization. FABP3 knockdown induces a young-like lipid composition in aged muscles, reduces ER stress, and improves protein synthesis and muscle recovery. Further, FABP3 reduces membrane fluidity and knockdown increases fluidity in vitro, potentially causing ER stress. Therefore, FABP3 drives membrane lipid composition-mediated ER stress to regulate muscle homeostasis during aging and is a valuable target for sarcopenia.All-inorganic metal halides perovskites (CsPbX3, X?=?Br or Cl) show strong excitonic and spin-orbital coupling effects, underpinning spin-selective excitonic transitions and therefore exhibiting great promise for spintronics and quantum-optics applications. Here we report spin-dependent optical nonlinearities in CsPbX3 single crystals by using ultrafast pump-probe spectroscopy. Many-body interactions between spin-polarized excitons act like a pseudo-magnetic field and thus lift the degeneracy of spin states resulting in a photoinduced circular dichroism. Such spontaneous spin splitting between "spin-up" and "spin-down" excitons can be several tens of milli-electron volts under intense excitations. The exciton spin relaxation time is ~20 picoseconds at very low pump fluence, the longest reported in the metal halides perovskites family at room temperature. The dominant spin-flip mechanism is attributed to the electron-hole exchange interactions. Our results provide essential understandings towards realizing practical spintronics applications of perovskite semiconductors.Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to model transportability. Here, we leverage the US PCORnet platform to develop an AKI prediction model and assess its transportability across six independent health systems. Our work demonstrates that cross-site performance deterioration is likely and reveals heterogeneity of risk factors across populations to be the cause. Therefore, no matter how accurate an AI model is trained at the source hospital, whether it can be adopted at target hospitals is an unanswered question. To fill the research gap, we derive a method to predict the transportability of AI models which can accelerate the adaptation process of external AI models in hospitals.Building electricity is a major component of global energy use and its environmental impacts. Detailed data on residential electricity use have many interrelated research applications, from energy conservation to non-intrusive load monitoring, energy storage, integration of renewables, and electric vs. fossil-based heating. The dataset presented here, Multifamily Residential Electricity Dataset (MFRED), contains the electricity use of 390 apartments, ranging from studios to four-bedroom units. All apartments are located in the Northeastern United States (IECC-climate-zone 4?A), but differ in their heating/cooling system and construction year (early to late 20th century). To adhere to privacy guidelines, data were averaged across 15 apartments each, based on annual electricity use. MFRED includes real and reactive power, at 10-second resolution, for January to December 2019 (246 million data points). The annual average real power per apartment is 343?W (3.27?W/m2 of floor area), with strong variation between seasons and apartment size. Considering its large number of apartments, high time resolution, real and reactive power, and 12-month duration, MFRED is currently unique for the multifamily-sector.Chiral optical materials based on circularly polarized luminescence (CPL) have emerged rapidly due to their feasible applications in diverse fields of research. However, limited to the small luminescence dissymmetry factor (glum), real application examples have rarely been reported. Here, we present a complex system, which show intense circularly polarized ultraviolet luminescence (CPUVL) with large glum value, enabling a chiral UV light triggered enantioselective polymerization. By integrating sensitized triplet-triplet annihilation upconversion and CPL, both visible-to-UV upconversion emission and upconverted circularly polarized ultraviolet luminescence (UC-CPUVL) were obtained in the systems, built of chiral annihilator R(S)-4,12-biphenyl[2,2]paracyclophane (R-/S-TP), and a thermally activated delayed fluorescence (TADF) sensitizer. After dispersing this upconversion system into room-temperature nematic liquid crystal, induced chiral nematic liquid crystal could significantly amplify the glum value (0.19) of UC-CPUVL. Further, the UC-CPUVL emission has been used to trigger the enantioselective photopolymerization of diacetylene. This work paves the way for the further development of functional application of CPL active materials.An amendment to this paper has been published and can be accessed via a link at the top of the paper.The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing?&gt;?3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted-modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. https://www.selleckchem.com/products/tuvusertib.html These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth-survival trade-off in driving tropical tree mortality.